Nacira Agram | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Nacira Agram | Mathematics | Best Researcher Award

Mathematics Department at KTH Royal, Algeria

Dr. Nacira Agram is an Associate Professor in the Department of Mathematics at KTH Royal Institute of Technology in Stockholm, Sweden. With a robust academic background and extensive research experience, her work primarily focuses on stochastic analysis, optimal control theory, and their applications in finance, insurance, and biology. Dr. Agram has made significant contributions to the field of applied mathematics, particularly in the study of stochastic differential equations and backward stochastic differential equations. Her research is characterized by a deep integration of theoretical mathematics with practical problem-solving, aiming to develop models that address real-world challenges. In addition to her research, Dr. Agram is actively involved in teaching and mentoring, guiding both master’s and doctoral students in their academic pursuits. Her international experience spans multiple countries, reflecting a commitment to fostering global academic collaborations and contributing to the advancement of mathematical sciences.

Professional Profile

Education

Dr. Agram’s academic journey began at the University of Biskra in Algeria, where she earned her Bachelor’s degree in Mathematics in 2008. She continued at the same institution to obtain her Master’s degree in Mathematics in 2010, focusing on stochastic analysis and optimal control. Her passion for these subjects culminated in a Ph.D. in Applied Mathematics from the University of Biskra in 2013, with a dissertation titled “Optimal Control in Infinite Time Horizon.” In 2021, Dr. Agram achieved the title of Docent from Linnaeus University in Växjö, Sweden, recognizing her substantial contributions to research and teaching in mathematics. This progression through rigorous academic training has equipped her with a solid foundation in both theoretical and applied aspects of mathematics, enabling her to tackle complex problems in her subsequent research and professional endeavors.

Professional Experience

Dr. Agram’s professional trajectory is marked by a series of esteemed positions across various academic institutions. Following her Ph.D., she served as an Associate Professor at the University of Biskra from 2014 to 2019, where she was instrumental in advancing the department’s research profile. She then pursued postdoctoral research at the University of Oslo in Norway between 2016 and 2018, collaborating on projects involving stochastic processes. In 2019, Dr. Agram joined Linnaeus University in Växjö, Sweden, as a Tenure-Track Assistant Professor, further honing her research and teaching skills. Her career advanced as she assumed the role of Associate Professor at KTH Royal Institute of Technology in March 2022, where she continues to contribute to the fields of probability, mathematical physics, and statistics. Throughout her career, Dr. Agram has demonstrated a commitment to academic excellence, interdisciplinary collaboration, and mentorship, impacting both her students and the broader mathematical community.

Research Interests

Dr. Agram’s research interests are centered around applied mathematics, with a particular emphasis on stochastic processes and optimal control theory. She delves into stochastic differential equations, backward stochastic differential equations, and partial differential equations, exploring their applications in various domains such as finance, insurance, and biology. Her work often involves the development of deep learning and reinforcement learning algorithms to solve complex optimal control problems, aiming to enhance decision-making processes in uncertain environments. Dr. Agram is also interested in the interplay between stochastic analysis and machine learning, seeking to leverage data-driven approaches to inform and improve mathematical models. Her interdisciplinary approach reflects a dedication to addressing practical problems through rigorous mathematical frameworks, contributing to advancements in both theory and application.

Research Skills

Dr. Agram possesses a diverse set of research skills that underpin her contributions to applied mathematics. She is proficient in stochastic modeling, adept at formulating and analyzing models that incorporate randomness to reflect real-world uncertainties. Her expertise extends to optimal control theory, where she develops strategies to influence dynamic systems towards desired objectives. Dr. Agram is skilled in the application of deep learning techniques, utilizing neural networks to approximate complex functions and solve high-dimensional problems. Her programming capabilities in Python, MATLAB, and C++ facilitate the implementation and simulation of mathematical models, enabling her to test hypotheses and validate theoretical findings. Additionally, her multilingual proficiency in Arabic, French, English, Norwegian, and Swedish enhances her ability to collaborate across diverse cultural and academic settings, fostering international research partnerships.

Awards and Honors

Throughout her career, Dr. Agram has been recognized for her academic excellence and research contributions. She has been the recipient of several prestigious grants, including a Starting Grant from KTH in 2024 amounting to 3 million SEK, and a VR Project Grant in 2020 totaling 3.6 million SEK, underscoring the significance and impact of her research endeavors. Her early academic achievements were marked by accolades such as the Best Bachelor Student Prize in 2008, Best Master Student Prize in 2010, and the First Ph.D. Defense Prize in 2013 from the University of Biskra, highlighting her consistent dedication to scholarly excellence. In 2017, Dr. Agram was selected to participate in the 5th Heidelberg Laureate Forum, an honor that connects promising researchers with laureates in mathematics and computer science, reflecting her standing in the global scientific community. These honors collectively attest to Dr. Agram’s sustained commitment to advancing mathematical sciences and her influence as a leading researcher in her field.

Conclusion

Dr. Nacira Agram exemplifies a distinguished scholar whose career seamlessly integrates rigorous research, dedicated teaching, and impactful mentorship. Her extensive work in stochastic analysis and optimal control has not only advanced theoretical mathematics but also provided practical solutions to complex problems in finance, insurance, and biology. Dr. Agram’s ability to secure significant research funding and her recognition through various awards underscore the value and relevance of her contributions to the scientific community. Her commitment to fostering international collaborations and guiding the next generation of mathematicians reflects a holistic approach to academia, where knowledge creation and dissemination go hand in hand. As she continues her tenure at KTH Royal Institute of Technology, Dr. Agram remains poised to make further strides in her research, inspiring both her peers and students through her exemplary dedication to the advancement of mathematical sciences.

Publication Top Notes

  1. “Deep learning for quadratic hedging in incomplete jump market”

    • Authors: Nacira Agram, Bernt Karsten Øksendal, Jan Rems
    • Year: 2024
    • Citations: 1

  2. “Optimal stopping of conditional McKean–Vlasov jump diffusions”

    • Authors: Nacira Agram, Bernt Karsten Øksendal
    • Year: 2024

Issa Bamia | Mathematics | Best Researcher Award

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Mr. Issa Bamia | Mathematics | Best Researcher Award

Data Scientist at African Institute for Mathematical Sciences, Mali.

Issa Bamia is a mathematician and data scientist with a deep passion for advancing research in adversarial machine learning and AI security. His expertise spans data engineering, digital health solutions, and cloud-based pipeline architecture, with a focus on addressing real-world issues in healthcare and telecommunications. With significant hands-on experience, Issa has optimized data collection processes, improved decision-making tools, and contributed to impactful projects that prioritize AI safety. His work as a data engineer for Muso Health demonstrates his commitment to using data-driven insights for tangible improvements in public health. Furthermore, he has a strong foundation in advanced data science and machine learning techniques, including proficiency with large language models (LLMs), security frameworks, and virtualization. This experience, combined with his commitment to ongoing research and development, positions Issa as a promising figure in the fields of AI safety and adversarial machine learning.

Professional Profile

Education

Issa Bamia holds a Master’s in Mathematical Sciences with a specialization in Data Science from the African Institute for Mathematical Sciences (AIMS), an institution renowned for its focus on African mathematicians and scientists. His education at AIMS included a rigorous curriculum that equipped him with the analytical and technical skills needed for advanced data science research and practical applications. He gained specialized knowledge in AI and adversarial machine learning, which he applied in his professional projects to develop data-driven solutions that impact digital health. Before this, he completed a Bachelor’s degree in Electronic Information Engineering from Tianjin University, where he gained foundational knowledge in data management and engineering principles. Issa’s educational background is complemented by certifications, including a professional certification in Large Language Models (LLMs) from Databricks, which has further refined his ability to work with complex AI models and large datasets. His diverse academic and practical training has laid a strong foundation for his research and professional pursuits in data science and AI security.

Professional Experience

Issa Bamia has a diverse professional background spanning data engineering, software development, and account management. Currently, he works as a data engineer for Muso Health, where he streamlines data collection, optimizes cloud-based data pipelines, and develops dashboards for real-time healthcare data analysis. His work here has been instrumental in improving medication stock management and reducing stockouts, enhancing healthcare delivery for underserved populations. Prior to this, Issa worked as an account manager with Huawei Technologies, where he customized technological solutions to meet telecom operators’ needs, ensuring smooth service delivery and strong client relations. Earlier, he was a software engineer with Whale Cloud Technologies, where he worked on the deployment and maintenance of cloud-based software products and managed system and database maintenance. Throughout these roles, Issa demonstrated an ability to handle complex data infrastructures and security protocols, showcasing his expertise in data science and its applications in both healthcare and telecommunications.

Research Interest

Issa Bamia’s primary research interests lie in adversarial machine learning, AI safety, and the development of secure, resilient AI models. His focus is on understanding and mitigating vulnerabilities in AI systems, particularly those posed by adversarial attacks, which can manipulate machine learning models to produce inaccurate or biased outcomes. He is passionate about exploring solutions that bolster the security and reliability of AI, especially in applications related to digital health, where data integrity is critical for decision-making. Issa is also interested in the ethical and practical implications of AI security, as well as the ongoing evolution of AI governance and control frameworks. Additionally, he seeks to apply his expertise in large language models (LLMs) to further enhance AI’s adaptability and reliability. His dedication to AI safety underscores a commitment to building AI systems that prioritize both performance and ethical responsibility, which is particularly significant in fields like healthcare, where secure and trustworthy AI systems are essential.

Research Skills

Issa possesses a robust set of research skills that are integral to his work in adversarial machine learning and AI security. He is proficient in cloud-based technologies and data pipeline design, with extensive experience in platforms such as Google Cloud Platform (GCP) and Apache Airflow. His technical repertoire includes advanced machine learning frameworks and tools for large language models (LLMs), containerization through Docker, and security protocols that support secure data architectures. In addition to data engineering skills, he has a strong command of SQL, NoSQL, Linux, and various programming languages including Python and JavaScript. Issa is adept at working with virtualization, networking, and incident response, which are crucial in managing and securing complex data systems. His hands-on experience with tools like Looker, Spark, and Hadoop further enhances his capability to analyze, optimize, and visualize large datasets, supporting his research pursuits in AI and data security. His skills in agile project tracking and stakeholder engagement also enable him to lead projects effectively and ensure that his research aligns with organizational goals.

Awards and Honors

Throughout his career, Issa has earned recognition for his contributions to data science and digital health innovation. His academic achievements include a Master’s degree in Mathematical Sciences (Data Science) from the African Institute for Mathematical Sciences (AIMS), an honor that highlights his academic commitment to data science research. While at AIMS, Issa developed a data-driven solution for medication stock management at Muso Health, a project that successfully reduced stockouts and improved patient care outcomes, marking a significant professional achievement in public health. His commitment to professional growth is also evident in his completion of the Databricks Professional Certificate in Large Language Models (LLMs), which reflects his proficiency in implementing, fine-tuning, and managing LLMs in various AI applications. This certification is a testament to his dedication to staying updated with advancements in AI, particularly in AI security, which is a key area of his research focus. These achievements underscore Issa’s commitment to both academic excellence and impactful, socially relevant research.

Conclusion

Issa Bamia’s background in adversarial machine learning, practical impact in digital health, and strong technical skill set make him a strong contender for the Best Researcher Award. His work on AI safety, coupled with impactful public health solutions, aligns well with the criteria for this award. Strengthening his research profile with further publications and collaborations would elevate his contributions in this competitive field. Overall, he demonstrates the qualities of an innovative and impactful researcher.